Random Number Generation in Java

Random Number Generation in Java

While developing applications, we often need to generate random numbers. Java provides support to generate random numbers primarily through the java.lang.Math and java.util.Random classes.

In this post, I will discuss different ways to generate random numbers based on different types of requirements.

Random Numbers using the Math Class

Java provides the Math class in the java.util package to generate random numbers.

The Math class contains the static Math.random()method to generate random numbers of double type. The random() method returns a double value with a positive sign, greater than or equal to 0.0 and less than 1.0. When you call Math.random(), under the hood, a java.util.Random pseudorandom-number generator object is created and used.

You can use the Math.random() method with or without passing parameters. If you provide parameters, the method produces random numbers within the given parameters.

The getRandomNumber() method uses the Math.random() method to return a positive double value, that is greater than or equal to 0.0 and less than 1.0.

The output of running the code is this.

Double between 0.0 and 1.0: SimpleRandomNumber = 0.21753313144345698

Random Numbers within a Given Range

For generating random numbers between a given a range, you need to specify the range. A standard expression for accomplishing this is:

(Math.random() * ((max - min) + 1)) + min

Let us break this expression into steps:

First, multiply the magnitude of the range of values you want to cover by the result that Math.random() produces.Math.random() * ( max – min )This returns a value in the range [0, max – min] where max is excluded. For example, if you want [5,10] you need to cover 5 integer values. So you can use Math.random()*5. This would return a value in the range [0,5], where 5 is not included.

Next, shift this range up to the range that you are targeting. You do this by adding the min value.

(Math.random() * ( max – min )) + min

But, this still does not include the maximum value.

To get the max value included, you need to add 1 to your range parameter (max – min). This will return a random double within the specified range.

double x = (Math.random()*((max-min)+1))+min;

There are different ways of implementing the above expression. Let us look at a couple of them.

Random Double within a Given Range

By default, the Math.random() method returns a random number of the type double whenever it is called. The code to generate a random double value between a specified range is this.

The preceding getRandomIntegerBetweenRange() method produces a random integer between the given range. As Math.random() method generates random numbers of double type, you need to truncate the decimal part and cast it to int in order to get the integer random number. You can call this method from the main method by passing the arguments as follow:

New Random Number Generation Features in Java 8

Java 8 has introduced a new method ints() in the java.util.Random class. The ints() method returns an unlimited stream of pseudorandom int values. You can limit the random numbers between a specified range by providing the minimum and the maximum values.

The code to use the Random.ints() method to generate random integer values within a specified range is this.

The getRandomNumberInts() method generates a stream of random integers between the min (inclusive) and max (exclusive). As ints() method produces an IntStream, the code calls the findFirst() method that returns an OptionalInt object that describes the first element of this stream. The code then calls the getAsInt() method to return the int value in OptionalInt.

The code to use the Random.ints() method to generate a stream of specified random integer values is this.

In addition to ints(), some other frequently used methods that Java 8 introduces to the Random class which can return a sequential stream of random numbers are:

LongStream longs()

DoubleStream doubles()

Summary

The java.util.Random class implements what is generally called a linear congruential generator (LCG). It is designed to be fast but does not meet requirements for real-time use. For example, use in unique session ID generation on a web server, scientific experiments, cryptography, or lotteries and sweepstakes where monetary stake is involved. For such scenarios, there are other alternatives, which I will cover in a later post.